To prevent forgery by copying, financial documents such as receipts, securities, and certificates are often preprinted with background patterns on which intended images such as characters are printed. When performing prescribed processing on documents preprinted with such background patterns, for example, when sorting the documents based on the printed images or when reading the characters using an OCR device (optical character reading device), the intended images printed on the documents must be accurately discriminated from the preprinted background patterns. However, since the density of the intended images and the density of the background patterns differ for different documents, it has been difficult to accurately discriminate the intended images from the background patterns.
In view of the above, there is proposed, in Japanese Laid-open Patent Publication No. 2007-28362, a check reading apparatus which removes a background pattern from image data acquired from a financial document such as a check and extracts only the contents of the document. To achieve this, the proposed check reading apparatus applies, to the original image data acquired by scanning the document, corrections so as to further increase the density of any pixel whose density is higher than its neighboring pixels and to further reduce the density of any pixel whose density is lower than its neighboring pixels. Then, the check reading apparatus creates a histogram representing the density distribution in the thus corrected image data, sets a binarization threshold somewhere between a crest appearing in a high-density region and a crest appearing in a low-density region, and performs binarization using the thus set binarization threshold.
On the other hand, in U.S. Pat. No. 6,507,670, there is proposed a system for removing a background pattern from a binary image. The proposed system divides the binary image into a plurality of image regions, calculates an image density value for each image region, counts the number of image regions associated with each image density value, selects as a threshold value an image density value that is lower than the image density value having the largest number of associated image regions, and setting any image region having an image density value smaller than the threshold value to zero.